[246517d] | 1 | #mono_gauss_coil model |
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| 2 | #conversion of DebyeModel.py |
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| 3 | #converted by Steve King, Mar 2016 |
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| 4 | |
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| 5 | |
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| 6 | |
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| 7 | r""" |
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| 8 | This model strictly describes the scattering from *monodisperse* polymer chains in theta solvents or polymer melts, conditions under which the distances between segments follow a Gaussian distribution. Provided the number of segments is large (ie, high molecular weight polymers) the single-chain form factor P(Q) is that described by Debye (1947). |
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| 9 | |
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| 10 | To describe the scattering from *polydisperse* polymer chains, see the To describe the scattering from *monodisperse* polymer chains, see the :ref:`poly_gauss_coil <poly-gauss-coil>` model. |
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| 11 | |
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| 12 | Definition |
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| 13 | ---------- |
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| 14 | |
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| 15 | *I(q)* = *scale* |cdot| *I* \ :sub:`0` |cdot| *P(q)* + *background* |
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| 16 | |
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| 17 | where |
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| 18 | |
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| 19 | *I*\ :sub:`0` = |phi|\ :sub:`poly` |cdot| *V* |cdot| (|rho|\ :sub:`poly` - |rho|\ :sub:`solv`)\ :sup:`2` |
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| 20 | |
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| 21 | *P(q)* = 2 [exp(-Z) + Z - 1] / Z \ :sup:`2` |
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| 22 | |
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| 23 | *Z* = (*q R* \ :sub:`g`)\ :sup:`2` |
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| 24 | |
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| 25 | and |
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| 26 | |
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| 27 | *V* = *M* / (*N*\ :sub:`A` |delta|) |
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| 28 | |
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| 29 | Here, |phi|\ :sub:`poly` is the volume fraction of polymer, *V* is the volume of a polymer coil, *M* is the molecular weight of the polymer, *N*\ :sub:`A` is Avogadro's Number, |delta| is the bulk density of the polymer, |rho|\ :sub:`poly` is the sld of the polymer, |rho|\ :sub:`solv` is the sld of the solvent, and *R*\ :sub:`g` is the radius of gyration of the polymer coil. |
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| 30 | |
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| 31 | The 2D scattering intensity is calculated in the same way as the 1D, but where the *q* vector is redefined as |
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| 32 | |
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| 33 | .. math:: |
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| 34 | |
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| 35 | q = \sqrt{q_x^2 + q_y^2} |
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| 36 | |
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| 37 | References |
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| 38 | ---------- |
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| 39 | |
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| 40 | P Debye, *J. Phys. Colloid. Chem.*, 51 (1947) 18. |
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| 41 | |
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| 42 | R J Roe, *Methods of X-Ray and Neutron Scattering in Polymer Science*, Oxford University Press, New York (2000). |
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| 43 | |
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| 44 | http://www.ncnr.nist.gov/staff/hammouda/distance_learning/chapter_28.pdf |
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| 45 | """ |
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| 46 | |
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| 47 | from numpy import inf, sqrt, exp |
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| 48 | |
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| 49 | name = "mono_gauss_coil" |
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| 50 | title = "Scattering from monodisperse polymer coils" |
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| 51 | |
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| 52 | description = """ |
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| 53 | Evaluates the scattering from |
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| 54 | monodisperse polymer chains. |
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| 55 | """ |
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| 56 | category = "shape-independent" |
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| 57 | |
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| 58 | # ["name", "units", default, [lower, upper], "type", "description"], |
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| 59 | parameters = [["i_zero", "1/cm", 70.0, [0.0, inf], "", "Intensity at q=0"], |
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| 60 | ["radius_gyration", "Ang", 75.0, [0.0, inf], "", "Radius of gyration"]] |
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| 61 | |
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| 62 | # NB: Scale and Background are implicit parameters on every model |
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| 63 | def Iq(q, i_zero, radius_gyration): |
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| 64 | # pylint: disable = missing-docstring |
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| 65 | z = (q * radius_gyration) * (q * radius_gyration) |
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| 66 | if (q == 0).any(): |
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| 67 | inten = i_zero |
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| 68 | else: |
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| 69 | inten = i_zero * 2.0 * (exp(-z) + z - 1.0 ) / (z * z) |
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| 70 | return inten |
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| 71 | #Iq.vectorized = True # Iq accepts an array of q values |
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| 72 | |
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| 73 | def Iqxy(qx, qy, *args): |
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| 74 | # pylint: disable = missing-docstring |
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| 75 | return Iq(sqrt(qx ** 2 + qy ** 2), *args) |
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| 76 | #Iqxy.vectorized = True # Iqxy accepts an array of qx, qy values |
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| 77 | |
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| 78 | demo = dict(scale = 1.0, |
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| 79 | i_zero = 70.0, |
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| 80 | radius_gyration = 75.0, |
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| 81 | background = 0.0) |
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| 82 | |
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| 83 | oldname = "DebyeModel" |
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| 84 | oldpars = dict(scale = 'scale', |
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| 85 | radius_gyration = 'rg', |
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| 86 | background = 'background') |
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| 87 | |
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| 88 | tests = [ |
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| 89 | [{'scale': 70.0, 'radius_gyration': 75.0, 'background': 0.0}, |
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| 90 | [0.0106939, 0.469418], [57.1241, 0.112859]], |
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| 91 | ] |
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